COVID-19 Data Analysis

Basic modeling with Real-World Data.

Author: Zachary Levonian

Repository Structure

A good entrypoint to this analyisis is the Jupyter notebook that explores the dataset or the Jupyter notebook that analyses the data by fitting multiple logistic regression models.

Otherwise, the directory layout is:

• notebook contains the analysis notebooks.
• src contains the covid_modeling Python package with helper functions and classes to support the analysis.
• tests contains pytest tests for the covid_modeling package.
• data is presumed to be the location of the input data... see the Data section below for more details.
• figures contains any images produced within the analysis notebooks.

Data

The data is a representative but fabricated sample of research data provided by ConcertAI. I don't have permission to share it publicly. Note that all PII is random in the data (e.g. names and addresses are random).

The structure of the data is visible in the analysis notebooks, and a sample is contained in the test resources (tests/resources/).

Installation

This repository uses poetry as its package manager, coordinated by make.

To install poetry and needed dependencies, run make install.

To run tests, run make test.

A few useful commands:

• poetry run <command> - Run the given command, e.g. poetry run pytest invokes the tests.
• source $(poetry env info --path)/bin/activate - An alternative to poetry shell that's less buggy in conda environments.